The age of autonomous artificial intelligence brought efficiency, but now demands accountability

The adoption of artificial intelligence in corporate environments has rapidly evolved from an auxiliary tool to a decisive business infrastructure. AI-based models already make decisions in credit processes, access management, risk sorting, resource allocation and contract review; often without active human supervision. But technological progress is about to collide with a new reality: that of a much more demanding global regulation.

While companies are still trying to create internal frameworks, the legislative world and regulatory bodies have already begun to define the limits of what will be acceptable. And the warning is clear: those who do not structure AI governance now will have to respond later for decisions that they do not know how to explain.

From self-regulation to active regulation: what is changing

The European Union has already approved the AI Act, the world's first comprehensive regulatory framework on AI systems, which establishes requirements such as risk assessment, algorithmic transparency, continuous governance and the possibility of external audit. At the same time, the Council of Europe launched the first international convention on AI, focusing on human rights and institutional responsibility.

In the US, although the federal regulatory movement is still under construction, states such as California and Colorado have already passed laws on decision automation. And there is a contrary movement, led by Republicans in the House, seeking to impose a 10-year moratorium on state laws on AI, as an attempt to standardize the arcaboose at the federal level.

Meanwhile, Asian countries such as China, South Korea and Japan are moving forward with their own regulations, especially on generative AI models and sensitive data analysis. The message is unequivocal: the cycle of unrestricted freedom of AI is over.

What's at stake for companies that already use AI behind the scenes

Many organizations have adopted AI in critical areas: internal auditing, fraud detection, access controls, predictive risk analysis, without revisiting their accountability models. But with the arrival of regulation, inevitable questions arise:

• What decisions were made by AI?

• In which processes has AI acted unsupervised?

• Who is responsible for the automated decision?

• How to audit a decision that is based on opaque machine learning?

The risk now lies not only in technical failure, but in the absence of traceability, explicability and accountability. Ignoring this can compromise audit reports, trigger regulatory penalties and erode stakeholder trust.

What is good AI governance and why it is not born suddenly

Effective AI governance requires three structural pillars:

1. Clear organizational architecture: definition of roles, responsibilities and limits for the use of AI. AI is not an isolated technical resource, but part of strategic decisions.
   

2. Traceability and documentation of automated decisions: who accessed, what data was used, what logic was applied, what results were generated.
   

3. Frameworks aligned with emerging requirements: such as ISO/IEC 42001:2023, NIST AI RMF and European guidelines on AI risk management.
   

How Vennx anticipates that future - today

At Vennx, AI governance is applied in practice. Solutions such as Oracle, created to monitor and correct access in real time based on business rules and compliance, operate with traceability, automation and auditable logic.

Different from tools that only organize data, solutions such as SoD Discovery, interprets access, identifies risks and suggests improvements based on artificial intelligence by crossing various records of functions and business rules, even detecting conflicts not mapped by human logic. This guarantees greater assertiveness and security against internal fraud.

Is your AI an advantage... or a hidden risk?

Artificial intelligence can be the engine of scalability, efficiency and predictive decision-making. More without governance, it can also be the source of errors, sanctions and loss of institutional credibility.

The question leaders need to ask now is not “are we using AI?”, but:
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“Are we governing this AI with the same rigor that we govern people and processes?”
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If the answer is no, the time to structure that base is now. And Vennx, as a specialist in the application of AI in regulated environments, can show how.

At Vennx, we believe that technology is only synonymous with security when it comes with intelligence and context. Talk to a Vennx Expertright now and discover how to revolutionize your access and compliance governance.

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